Relevant bibliographies by topics / Addresses (data processing)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Addresses (data processing)'

Author: Grafiati
Published: 29 July 2024
Last updated: 31 July 2025

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Journal articles on the topic "Addresses (data processing)"

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Johnson, Sarah L. "Quantum Machine Learning Algorithms for Big Data Processing." International Journal of Innovative Computer Science and IT Research 1, no. 02 (2025): 1–11. https://doi.org/10.63665/ijicsitr.v1i02.04.

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Quantum Machine Learning (QML) is a new discipline that unites artificial intelligence and quantum computing and can address computational problems of big data analysis. Traditional machine learning algorithms may be pushed to their limits in dealing with the increased complexity and scale of today's data sets and thus are unable to find useful insights within a reasonable time frame. Quantum computing, capable of tapping quantum mechanical processes like superposition and entanglement, is capable of turning this field upside down. In this paper, the concepts behind quantum computing are discu
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Chanda, Deepak. "Automated ETL Pipelines for Modern Data Warehousing: Architectures, Challenges, and Emerging Solutions." Eastasouth Journal of Information System and Computer Science 1, no. 03 (2024): 209–12. https://doi.org/10.58812/esiscs.v1i03.523.

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The paper addresses the evolution of automated Extract, Transform, Load (ETL) pipelines in contemporary data warehousing environments, highlighting their essential role in enabling timely analytics and business intelligence. Recent architectural approaches like cloud-native ETL, stream processing architectures, and metadata-driven automation are addressed in the context of increasing data volume and variety. The article addresses typical challenges like schema evolution management, data quality assurance, and cross-platform integration in the context of discussing novel solutions based on leve
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Researcher. "REAL-TIME DATA PROCESSING IN MICROSERVICES ARCHITECTURES." International Journal of Computer Engineering and Technology (IJCET) 15, no. 6 (2024): 760–73. https://doi.org/10.5281/zenodo.14228620.

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Real-time data processing in modern distributed systems has evolved significantly, transforming how organizations across various sectors handle operational demands. This comprehensive article explores the fundamental aspects of real-time processing in microservices architectures, examining key technological advancements, implementation strategies, and architectural patterns. The article investigates the impact of event-driven architectures, message brokers, and stream processing technologies while detailing best practices for maintaining data consistency and system performance. Examining cloud
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Romanchuk, Vitaliy. "Mathematical support and software for data processing in robotic neurocomputer systems." MATEC Web of Conferences 161 (2018): 03004. http://dx.doi.org/10.1051/matecconf/201816103004.

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The paper addresses classification and formal definition of neurocomputer systems for robotic complexes, based on the types of associations among their elements. We suggest analytical expressions for performance evaluation in neural computer information processing, aimed at development of methods, algorithms and software that optimize such systems.
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Hahanov, V. I., V. H. Abdullayev, S. V. Chumachenko, E. I. Lytvynova, and I. V. Hahanova. "IN-MEMORY INTELLIGENT COMPUTING." Radio Electronics, Computer Science, Control, no. 1 (April 2, 2024): 161. http://dx.doi.org/10.15588/1607-3274-2024-1-15.

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Context. Processed big data has social significance for the development of society and industry. Intelligent processing of big data is a condition for creating a collective mind of a social group, company, state and the planet as a whole. At the same time, the economy of big data (Data Economy) takes first place in the evaluation of processing mechanisms, since two parameters are very important: speed of data processing and energy consumption. Therefore, mechanisms focused on parallel processing of large data within the data storage center will always be in demand on the IT market.
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Gururaj T. and Siddesh G. M. "Hybrid Approach for Enhancing Performance of Genomic Data for Stream Matching." International Journal of Cognitive Informatics and Natural Intelligence 15, no. 4 (2021): 1–18. http://dx.doi.org/10.4018/ijcini.20211001.oa38.

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In gene expression analysis, the expression levels of thousands of genes are analyzed, such as separate stages of treatments or diseases. Identifying particular gene sequence pattern is a challenging task with respect to performance issues. The proposed solution addresses the performance issues in genomic stream matching by involving assembly and sequencing. Counting the k-mer based on k-input value and while performing DNA sequencing tasks, the researches need to concentrate on sequence matching. The proposed solution addresses performance issue metrics such as processing time for k-mer count
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Sun, Xihuang, Peng Liu, Yan Ma, Dingsheng Liu, and Yechao Sun. "Streaming Remote Sensing Data Processing for the Future Smart Cities." International Journal of Distributed Systems and Technologies 7, no. 1 (2016): 1–14. http://dx.doi.org/10.4018/ijdst.2016010101.

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The explosion of data and the increase in processing complexity, together with the increasing needs of real-time processing and concurrent data access, make remote sensing data streaming processing a wide research area to study. This paper introduces current situation of remote sensing data processing and how timely remote sensing data processing can help build future smart cities. Current research on remote sensing data streaming is also introduced where the three typical and open-source stream processing frameworks are introduced. This paper also discusses some design concerns for remote sen
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Nguyen, Minh Duc. "A Scientific Workflow System for Satellite Data Processing with Real-Time Monitoring." EPJ Web of Conferences 173 (2018): 05012. http://dx.doi.org/10.1051/epjconf/201817305012.

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This paper provides a case study on satellite data processing, storage, and distribution in the space weather domain by introducing the Satellite Data Downloading System (SDDS). The approach proposed in this paper was evaluated through real-world scenarios and addresses the challenges related to the specific field. Although SDDS is used for satellite data processing, it can potentially be adapted to a wide range of data processing scenarios in other fields of physics.
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Prabagar, S., Vinay K. Nassa, Senthil V. M, Shilpa Abhang, Pravin P. Adivarekar, and Sridevi R. "Python-based social science applications’ profiling and optimization on HPC systems using task and data parallelism." Scientific Temper 14, no. 03 (2023): 870–76. http://dx.doi.org/10.58414/scientifictemper.2023.14.3.48.

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This research addresses the pressing need to optimize Python-based social science applications for high-performance computing (HPC)systems, emphasizing the combined use of task and data parallelism techniques. The paper delves into a substantial body of research,recognizing Python’s interpreted nature as a challenge for efficient social science data processing. The paper introduces a Pythonprogram that exemplifies the proposed methodology. This program uses task parallelism with multi-processing and data parallelismwith dask to optimize data processing workflows. It showcases how researchers c
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Krishnamurthi, Rajalakshmi, Adarsh Kumar, Dhanalekshmi Gopinathan, Anand Nayyar, and Basit Qureshi. "An Overview of IoT Sensor Data Processing, Fusion, and Analysis Techniques." Sensors 20, no. 21 (2020): 6076. http://dx.doi.org/10.3390/s20216076.

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In the recent era of the Internet of Things, the dominant role of sensors and the Internet provides a solution to a wide variety of real-life problems. Such applications include smart city, smart healthcare systems, smart building, smart transport and smart environment. However, the real-time IoT sensor data include several challenges, such as a deluge of unclean sensor data and a high resource-consumption cost. As such, this paper addresses how to process IoT sensor data, fusion with other data sources, and analyses to produce knowledgeable insight into hidden data patterns for rapid decision
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Dissertations / Theses on the topic "Addresses (data processing)"

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Fowler, Robert Joseph. "Decentralized object finding using forwarding address /." Thesis, Connect to this title online; UW restricted, 1985. http://hdl.handle.net/1773/6947.

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Underwood, Ian. "An nMOS addressed liquid crystal spatial light modulator." Thesis, University of Edinburgh, 1987. http://hdl.handle.net/1842/1542.

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Coherent optical data processing is recognised, for many applications, as a viable alternative to digital electronic signal processing; the case for using coherent optics is particularly strong when the data to be processed is two dimensional in nature. It has long been accpeted that, in order for coherent optical processing to achieve its full performance potential, two dimensional spatial light modulators - capable of operating in real time - are essential at both the object plane (where the data is input to the system) and the Fourier plane (where the operation carried out on the data is de
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Young, Jeffrey Scott. "Global address spaces for efficient resource provisioning in the data center." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50261.

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The rise of large data sets, or "Big Data'', has coincided with the rise of clusters with large amounts of memory and GPU accelerators that can be used to process rapidly growing data footprints. However, the complexity and performance limitations of sharing memory and accelerators in a cluster limits the options for efficient management and allocation of resources for applications. The global address space model (GAS), and specifically hardware-supported GAS, is proposed as a means to provide a high-performance resource management platform upon which resource sharing between nodes and resourc
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Suddath, Suzanne Virginia. "Engaging girls in the use of technology : codifying software design characteristics that address girls' needs." Thesis, Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/17522.

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Scarlato, Michele. "Sicurezza di rete, analisi del traffico e monitoraggio." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amslaurea.unibo.it/3223/.

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Il lavoro è stato suddiviso in tre macro-aree. Una prima riguardante un'analisi teorica di come funzionano le intrusioni, di quali software vengono utilizzati per compierle, e di come proteggersi (usando i dispositivi che in termine generico si possono riconoscere come i firewall). Una seconda macro-area che analizza un'intrusione avvenuta dall'esterno verso dei server sensibili di una rete LAN. Questa analisi viene condotta sui file catturati dalle due interfacce di rete configurate in modalità promiscua su una sonda presente nella LAN. Le interfacce sono due per potersi interfacciar
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Bailey, Peter Richard. "Process-oriented language design for distributed address spaces." Phd thesis, 1997. http://hdl.handle.net/1885/145990.

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Books on the topic "Addresses (data processing)"

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United States. Congress. House. Committee on Government Reform. Subcommittee on the Census. Oversight of the 2000 census: A midterm evaluation of the local update of census addresses program : hearing before the Subcommittee on the Census of the Committee on Government Reform, House of Representatives, One Hundred Sixth Congress, first session, September 29, 1999. U.S. G.P.O., 2000.

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Fister, Mark. A pocket tour of money on the Internet. Sybex, 1995.

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Subcommittee, Maryland State Government Geographic Information Coordinating Committee Database and Resource Development. Recommendations on addressing in support of address matching and geocoding: Adopted April 12, 1995. The Committee, 1995.

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Cindy, Yager, ed. Writer's guide to Internet resources. Macmillan, USA, 1998.

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Briggs-Erickson, Carol. Environmental guide to the Internet. 2nd ed. Government Institutes, Inc., 1996.

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Briggs-Erickson, Carol. Environmental guide to the Internet. 3rd ed. Government Institutes, Inc., 1997.

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Daniel, Levinson, ed. Computer applications in clinical practice: An overview. Macmillan Pub. Co., 1985.

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J, Evans David, and Meeting on the Advanced Research Topic "Sparsity and Its Applications" (1983 : University of Technology, Loughborough, England), eds. Sparsity and its applications. Cambridge University Press, 1985.

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Winer, Dov. Global Jewish networking handbook. Department of Information, World Zionist Organization, 1994.

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Liu, Cricket. DNS and BIND cookbook. O'Reilly, 2002.

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Book chapters on the topic "Addresses (data processing)"

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Vasiliu, Laurenţiu, Dumitru Roman, and Radu Prodan. "Extreme and Sustainable Graph Processing for Green Finance Investment and Trading." In AI, Data, and Digitalization. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53770-7_8.

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AbstractThe Graph-Massivizer project, funded by the Horizon Europe research and innovation program, aims to create a high-performance and sustainable platform for extreme data processing. This paper focuses on one use case that addresses the limitations of financial market data for green and sustainable investments. The project allows for the fast, semi-automated creation of realistic and affordable synthetic (extreme) financial datasets of any size for testing and improving AI-enhanced financial algorithms for green investment and trading. Synthetic data usage removes biases, ensures data aff
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Reshadat, Vahideh, Tess Kolkman, Kalliopi Zervanou, et al. "Knowledge Modeling and Incident Analysis for Special Cargo." In Technologies and Applications for Big Data Value. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78307-5_23.

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AbstractThe airfreight industry of shipping goods with special handling needs, also known as special cargo, suffers from nontransparent shipping processes, resulting in inefficiency. The LARA project (Lane Analysis and Route Advisor) aims at addressing these limitations and bringing innovation in special cargo route planning so as to improve operational deficiencies and customer services. In this chapter, we discuss the special cargo domain knowledge elicitation and modeling into an ontology. We also present research into cargo incidents, namely, automatic classification of incidents in free-t
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Papakonstantinou, Mihalis, Manos Karvounis, Giannis Stoitsis, and Nikos Manouselis. "Deploying a Scalable Big Data Platform to Enable a Food Safety Data Space." In Data Spaces. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98636-0_11.

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AbstractThe main goal of this chapter is to share the technical details and best practices for setting up a scalable Big Data platform that addresses the data challenges of the food industry. The amount of data that is generated in our food supply chain is rapidly increasing. The data is published by hundreds of organizations on a daily basis, in many different languages and formats making its aggregation, processing, and exchange a challenge. The efficient linking and mining of the global food data can enable the generation of insights and predictions that can help food safety experts to make
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Hanssen, Geir Kjetil, and Martin Gilje Jaatun. "Agile Approaches in Critical Infrastructures." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-72781-8_9.

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AbstractThis paper explores the emergence of agile-inspired approaches in the critical infrastructure sector, with a focus on the current digital transformation of the Norwegian Oil & Gas industry. It addresses how traditional plan-driven development and strict architectural principles are challenged by the need to exploit the growing volume of operational data, in search for better, faster, and safer operations. We emphasize the increasing reliance on data for optimizing operations and the inherent risks and culture clashes between Information Technology (IT) and Operational Technology (O
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Serrano, Maria A., César A. Marín, Anna Queralt, et al. "An Elastic Software Architecture for Extreme-Scale Big Data Analytics." In Technologies and Applications for Big Data Value. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78307-5_5.

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AbstractThis chapter describes a software architecture for processing big-data analytics considering the complete compute continuum, from the edge to the cloud. The new generation of smart systems requires processing a vast amount of diverse information from distributed data sources. The software architecture presented in this chapter addresses two main challenges. On the one hand, a new elasticity concept enables smart systems to satisfy the performance requirements of extreme-scale analytics workloads. By extending the elasticity concept (known at cloud side) across the compute continuum in
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Daniel, João, Gabriel Mota, Xiaofeng Wang, and Eduardo Guerra. "Architecture Refactoring Towards Service Reusability in the Context of Microservices." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-94544-1_9.

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Abstract Agility embraces changes in the functional and non-functional requirements. When the latter happens, the architecture needs to evolve, putting architectural refactoring in evidence. Microservices is an architectural style that enables more agility in a system’s architecture, as it favors the evolution of the system by adding new operations. But it also has its liabilities: the number of services can explode, with similar ones being created. Ultimately, that harms the system’s evolution and maintenance. This work addresses these challenges by proposing a catalog of architecture refacto
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Ueck, Hannes, Robert Andrews, Moe T. Wynn, and Sander J. J. Leemans. "Differentially Private Event Logs with Case Attributes." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-82225-4_18.

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Abstract Event logs capture the execution of processes, record activities and additional information. A trace represents a single instance of a process and includes a sequence of activity records and case attributes with additional information. Event logs may contain sensitive personal information that could harm an individual’s privacy if it is published without pre-processing. Differential privacy (DP) limits the disclosure of new information about any individual when publishing an event log beyond the publicly available background knowledge. Many privacy-preserving approaches to event log p
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Kashkevich, Svitlana, Oleksiy Buyalo, Olha Matsyi, Anastasiia Voznytsia, Daniil Krant, and Kostiantin Radchenko. "Scientific and methodological apparatus for processing diverse data in automated control systems." In DECISION SUPPORT SYSTEMS: MATHEMATICAL SUPPORT. TECHNOLOGY CENTER PC, 2025. https://doi.org/10.15587/978-617-8360-13-9.ch4.

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This section of the study proposes the conceptual foundations for the use of artificial intelligence in intelligent decision support systems. In the course of the research, the authors:– justified the feasibility of using artificial intelligence theory for processing heterogeneous data in automated control systems;– developed a methodology for data distribution in automated control systems;– designed a model for evaluating the process of heterogeneous data processing in automated troop control systems using expert information;– improved the methodology for configuring an information system to
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Stotz, Nils, and Paul Drews. "Metrics for Experimentation Programs: Categories, Benefits and Challenges." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-94544-1_15.

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Abstract Experimentation programs are vital for enabling data-driven decision-making within product development. However, evaluating their overarching success remains a significant challenge. Current metrics, such as conversion rates, primarily focus on individual experiments, leaving a gap in assessing broader program efficiency and impact. This paper addresses this gap by presenting a structured overview and analysis of 18 program-level metrics, categorized into six domains: Volume, Outcome-Based, Quality, Engagement, Process Efficiency and Strategic Alignment. Metrics such as experimentatio
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Kotze, Haidee, Minna Korhonen, Adam Smith, and Bertus van Rooy. "Chapter 2. Salient differences between Australian oral parliamentary discourse and its official written records." In Exploring Language and Society with Big Data. John Benjamins Publishing Company, 2023. http://dx.doi.org/10.1075/scl.111.02kot.

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This chapter addresses the question of editorial practice for the Australian Hansard with the use of an aligned corpus of transcribed audio recordings and the corresponding Hansard records, covering the period 1946–2015. A more traditional, qualitative, bottom-up approach is taken by manually analysing the data to compile a list of differences in the two types of records. In addition, a deductive, quantitative approach is adopted by using the multidimensional analysis method of Biber (1988) to identify significant differences in the frequencies of (clusters of) features between the oral transc
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Conference papers on the topic "Addresses (data processing)"

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Santana, Vinicius, Andr�s Riedemann, Pierre J. Walker, and Idelfonso Nogueira. "Langmuir.jl: An Efficient and composable Julia Package for Adsorption Thermodynamics." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.144752.

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Recent advancements in material design have made adsorption a more energy-efficient alternative to traditional thermally driven separation processes. Accurate modelling of adsorption thermodynamics is crucial for designing and operating equilibrium-limited adsorption systems. High-quality open-source packages like PyIAST, PyGAPsare available for processing adsorption data in Python. They provide a robust set of features for processing and analysing isotherms. However, they have no support for automatic differentiation and are not targeted for performance. Langmuir.jl addresses these limitation
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Pile, Santa, Oleg Lesota, Silvan David Peter, Christina Humer, and Martin Di Gasser. "Spin-Wave Voices: Sonification of Nanoscale Spin Waves as an Engagement and Research Tool." In ICAD 2024: The 29th International Conference on Auditory Display. International Community for Auditory Display, 2024. http://dx.doi.org/10.21785/icad2024.024.

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Magnonics is an emerging research field that addresses the use of spin waves (magnons), purely magnetic waves, for information transport and processing. Spin waves are a potential replacement for electric current in novel computational devices that would make them more compact and energy effcient. The field is yet little known, even among physicists. Additionally, with the development of new measuring techniques and computational physics, the obtained magnetic data becomes more complex, in some cases including 3D vector fields and time-resolution. This work presents an approach to the audio-vi
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Huang, Kuan-Che, David Shan-Hill Wong, and Yuan Yao. "Predicting Final Properties in Ibuprofen Production with Variable Batch Durations." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.146695.

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This study addresses the challenge of predicting final properties in batch processes with highly uneven durations, using the ibuprofen production process as a case study. Novel methodologies are proposed and compared against traditional regression algorithms, which rely on batch trajectory synchronization as a pre-processing step. The performance of each method is evaluated using established metrics. The data for this study were generated using Aspen Plus V12 simulation software, focused on batch reactors. To handle the unequal-length trajectories in batch processes, this research constructs a
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Thomas, M. J. J. Simon, P. B. Hebert, K. G. Jordan, and S. E. Lorimer. "Inhibition of Sweet Corrosion in Subsea Flowlines." In CORROSION 1998. NACE International, 1998. https://doi.org/10.5006/c1998-98057.

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Abstract Corrosion inhibition is the principal means of corrosion control in sweet service flowlines between subsea wells and processing platforms in the Gulf of Mexico. In view of the temperatures and the well conditions, hydrate control chemicals have to be injected as well. The paper addresses the challenges of selecting corrosion inhibitors that are suitable for the prevailing flowline conditions, are compatible with hydrate inhibition, and with the materials of the subsea umbilical. Initial experience based on limited field monitoring data is reviewed. Key findings include the need to car
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Gol, Kursat, and Metin Salihmuhsin. "Statistical data acquisition via filtering URL addresses with NetFPGA open source hardware platform." In 2016 24th Signal Processing and Communication Application Conference (SIU). IEEE, 2016. http://dx.doi.org/10.1109/siu.2016.7495798.

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Mohammed Ali, Sura I. "Data Processing: An Approach Based On Indexing." In XI. International Scientific Congress of Pure, Applied and Technological Sciences (MINAR Congress). Rimar Academy, 2024. https://doi.org/10.47832/minarcongress11-6.

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The way things operate on the web has shifted because of advancements, in the Semantic Web and linked data. The use of the Standard Resource Description Framework (RDF) is widespread for storing data. Since RDF follows a graph based data model organizing and accessing information poses challenges. This necessitates the development of large scale systems that offer ways to search and retrieve information for use by both humans and machines. Our proposed approach seeks to address these issues by introducing an indexing engine tailor made for RDF structures. To enhance data retrieval speed and qu
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Zhao, Qizhen, and Tochi Onuegbu. "WorkTune: A Music-Assisted Writing Efficiency Evaluation and Promotion Platform using Artificial Intelligence and Natural Language Processing." In 5th International Conference on Artificial Intelligence and Big Data. Academy & Industry Research Collaboration Center, 2024. http://dx.doi.org/10.5121/csit.2024.140423.

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In a world where music accompanies various tasks, our paper addresses the challenge of understanding the impact of background music on work efficiency. The background problem centers on the lack of precision in existing studies, overlooking individual preferences and work types. Our proposed solution is a Python-based application that evaluates an individual's work efficiency while listening to different music genres [1]. The user-friendly interface incorporates features like music category selection, login options, and real-time statistics tracking [2][3]. Challenges, such as diverse user int
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Jenkins, R. Brian, and Bradley D. Clymer. "Acoustooptic comparison switch with polarization multiplexed analog addressing." In OSA Annual Meeting. Optica Publishing Group, 1991. http://dx.doi.org/10.1364/oam.1991.wu2.

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Switching networks based on perfect shuffle or Banyan interconnection techniques are useful in parallel processing and telecommunications. The integral components in these networks are the comparison switches that control the routing of data through the network. An acoustooptic comparison switch has been implemented that simplifies control using analog addressing techniques and insures high-bandwidth data transmission by multiplexing the data and the address on orthogonal polarizations of light. The addresses can be easily extracted and processed apart from the data using polarizing beam split
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Bi, Athena, and Carlos Gonzalez. "A Comprehensive Web Application for Art Showcasing Utilizing Generative AI for Art Therapy Applications." In 6th International Conference on Artificial Intelligence and Big Data. Academy & Industry Research Collaboration Center, 2025. https://doi.org/10.5121/csit.2024.150113.

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Art therapy is a proven method for fostering self-expression and supporting mental health, yet traditional approaches often require resource-intensive, manual analysis by therapists, limiting accessibility [1]. Our project addresses this gap by creating an AI-powered art therapy web application that enables users to upload artwork and receive personalized, therapeutic insights. By combining Firebase for user management, Python Flask for backend processing, and OpenAI for generating art interpretations, our platform bridges the expressive power of art with the analytical capabilities of AI [2].
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Gomzov, N. "PROCESSING OF GRAPHIC AND LEXICAL INFORMATION FOR THE FORMATION OF KNOWLEDGE BASES ON LANDSCAPES." In CHALLENGING ISSUES IN SYSTEMS MODELING AND PROCESSES. FSBE Institution of Higher Education Voronezh State University of Forestry and Technologies named after G.F. Morozov, 2025. https://doi.org/10.58168/cismp2024_34-39.

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The article addresses the problem of processing graphic and lexical information for the formation of knowledge bases on landscapes. It considers the possibility of using a neuro-fuzzy network, which enables effective processing of heterogeneous data and obtaining more accurate analysis results.
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Reports on the topic "Addresses (data processing)"

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Pasupuleti, Murali Krishna. AI-Driven Marketing Innovations: Personalization and Ethics in the Digital Era. National Education Services, 2025. https://doi.org/10.62311/nesx/rr625.

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Abstract: This article explores the transformative impact of artificial intelligence (AI) on digital marketing, focusing on strategies for delivering personalized content and ensuring ethical advertising. By leveraging AI, marketers can now analyze consumer behavior with precision, enabling targeted content, automated ad placement, and real-time adjustments that enhance user engagement and conversions. The Article examines foundational AI techniques, such as recommendation engines, predictive analytics, and natural language processing, which drive personalization at scale. Additionally, it add
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Pasupuleti, Murali Krishna. 2D Quantum Materials for Next-Gen Semiconductor Innovation. National Education Services, 2025. https://doi.org/10.62311/nesx/rrvi425.

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Abstract The emergence of two-dimensional (2D) quantum materials is revolutionizing next-generation semiconductor technology, offering superior electronic, optical, and quantum properties compared to traditional silicon-based materials. 2D materials, such as graphene, transition metal dichalcogenides (TMDs), hexagonal boron nitride (hBN), and black phosphorus, exhibit high carrier mobility, tunable bandgaps, exceptional mechanical flexibility, and strong light-matter interactions, making them ideal candidates for ultra-fast transistors, spintronics, optoelectronic devices, and quantum computin
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Tayeb, Shahab. Taming the Data in the Internet of Vehicles. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2014.

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As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and f
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Guo, Ge, Jiageng Liu, and Guangheng Liu. Multi-sensor Fusion-based Vehicle Localization. SAE International, 2024. http://dx.doi.org/10.4271/epr2024023.

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<div class="section abstract"><div class="htmlview paragraph">Multi-sensor fusion (MSF) is believed to be a promising tool for vehicular localization in urban environments. Due to the differences in principles and performance of various onboard vehicle sensors, MSF inevitably suffers from heterogeneous sources and vulnerability to cyber-attacks. Therefore, an essential requirement of MSF is the capability of providing a consumer-grade solution that operates in real-time, is accurate, and immune to abnormal conditions with guaranteed performance and quality of service for location-b
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van der Sloot, Bart. The Quality of Life: Protecting Non-personal Interests and Non-personal Data in the Age of Big Data. Universitätsbibliothek J. C. Senckenberg, Frankfurt am Main, 2021. http://dx.doi.org/10.21248/gups.64579.

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Under the current legal paradigm, the rights to privacy and data protection provide natural persons with subjective rights to protect their private interests, such as related to human dignity, individual autonomy and personal freedom. In principle, when data processing is based on non-personal or aggregated data or when such data pro- cesses have an impact on societal, rather than individual interests, citizens cannot rely on these rights. Although this legal paradigm has worked well for decades, it is increasingly put under pressure because Big Data processes are typically based indis- crimin
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Ruby, Jeffrey, Robert Fischer, Richard Massaro, et al. Optimization strategies for geospatial data on end-user devices. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49359.

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The ability to quickly disseminate geospatial data across all echelons, particularly those at the tactical edge, is critical to meeting threats described by the Multi-Domain Operations doctrine. The US Army Engineer Research and Development Center, Geospatial Research Laboratory (ERDC-GRL), is researching the optimization of the formats, data models, file sizes, and quality of geospatial products to be exploited by end-user devices (EUDs). This report describes a processing methodology comprising custom software and open-source tools to optimize Army Geospatial Enterprise Standard Sharable Geo
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Ruby, Jeffrey, Robert Fischer, Richard Massaro, et al. Optimization strategies for geospatial data on end-user devices. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49366.

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The ability to quickly disseminate geospatial data across all echelons, particularly those at the tactical edge, is critical to meeting threats described by the Multi-Domain Operations doctrine. The US Army Engineer Research and Development Center, Geospatial Research Laboratory (ERDC-GRL), is researching the optimization of the formats, data models, file sizes, and quality of geospatial products to be exploited by end-user devices (EUDs). This report describes a processing methodology comprising custom software and open-source tools to optimize Army Geospatial Enterprise Standard Sharable Geo
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Guicheney, William, Tinashe Zimani, Hope Kyarisiima, and Louisa Tomar. Big Data in the Public Sector: Selected Applications and Lessons Learned. Inter-American Development Bank, 2016. http://dx.doi.org/10.18235/0007024.

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This paper analyzes different ways in which big data can be leveraged to improve the efficiency and effectiveness of government. It describes five cases where massive and diverse sets of information are gathered, processed, and analyzed in three different policy areas: smart cities, taxation, and citizen security. The cases, compiled from extensive desk research and interviews with leading academics and practitioners in the field of data analytics, have been analyzed from the perspective of public servants interested in big data and thus address both the technical and the institutional aspects
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Ruby, Jeffrey, Richard Massaro, John Anderson, and Robert Fischer. Three-dimensional geospatial product generation from tactical sources, co-registration assessment, and considerations. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/46442.

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According to Army Multi-Domain Operations (MDO) doctrine, generating timely, accurate, and exploitable geospatial products from tactical platforms is a critical capability to meet threats. The US Army Corps of Engineers, Engineer Research and Development Center, Geospatial Research Laboratory (ERDC-GRL) is carrying out 6.2 research to facilitate the creation of three-dimensional (3D) products from tactical sensors to include full-motion video, framing cameras, and sensors integrated on small Unmanned Aerial Systems (sUAS). This report describes an ERDC-GRL processing pipeline comprising custom
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Zhao, George, Grang Mei, Bulent Ayhan, Chiman Kwan, and Venu Varma. DTRS57-04-C-10053 Wave Electromagnetic Acoustic Transducer for ILI of Pipelines. Pipeline Research Council International, Inc. (PRCI), 2005. http://dx.doi.org/10.55274/r0012049.

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In this project, Intelligent Automation, Incorporated (IAI) and Oak Ridge National Lab (ORNL) propose a novel and integrated approach to inspect the mechanical dents and metal loss in pipelines. It combines the state-of-the-art SH wave Electromagnetic Acoustic Transducer (EMAT) technique, through detailed numerical modeling, data collection instrumentation, and advanced signal processing and pattern classifications, to detect and characterize mechanical defects in the underground pipeline transportation infrastructures. The technique has four components: (1) thorough guided wave modal analysis
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